McKinsey’s ConsumerWise research — drawn from surveys of 25,000+ consumers across multiple quarters — describes the US consumer in 2026 with more granularity than any single macro data point. Income is the strongest differentiator of confidence. Gen Z is financially strained despite surface-level optimism signals. Savings are being depleted. Credit card use is rising. And AI is beginning to reshape how consumers make financial decisions before they ever contact a lender. Here is the full read for consumer lending executives.
McKinsey’s ConsumerWise research program — which has surveyed more than 25,000 consumers across 18 countries on a quarterly basis since the pandemic — published its latest State of the US Consumer report this week. It is the most methodologically rigorous ongoing consumer sentiment and behavior dataset available outside of federal statistical agencies. The findings for consumer lenders are specific, granular, and in some cases directly contrary to the macro narrative that dominates financial news. Here is the precise read.
McKinsey’s Q1 2026 ConsumerWise data makes the bifurcation thesis quantitatively explicit in a way that earnings call commentary and sentiment surveys only approximate. The finding: income is the strongest differentiator of economic confidence among US consumers — stronger than age, stronger than geography, stronger than employment sector. On average, the wealthier the consumer, the more optimistic they report feeling. The relationship is monotonic and consistent across every quarter McKinsey has surveyed since mid-2024.
This is not a new finding in direction — the bifurcated consumer has been described by every major bank management team, every large CPG company CEO, and every Fed district report since Q4 2025. What McKinsey’s data adds is precision. The income-confidence gradient is not a story about the top 10% versus everyone else. It is a continuous gradient across the income distribution, with each income decile showing meaningfully lower confidence than the one above it. The implication for consumer lenders is that credit risk does not cluster at a single FICO threshold or income cutoff — it is distributed along a continuous income gradient, with stress intensifying as you move down the distribution.
The ConsumerWise Q1 2026 data (covering the first weeks of January and February — before the Iran war began on February 28) showed consumer sentiment “remained relatively flat” compared to late 2025, with a slightly smaller share of pessimists and a slightly larger share of neutral-or-mixed respondents. The Q4 2025 data, by contrast, showed a 16-point swing in net optimism — the percentage of optimists fell seven points while pessimists rose nine points — driven by persistent inflation concerns and a softening labor market perception.
The January-February stability in the Q1 data was the last clean sentiment read before the energy shock. The University of Michigan data — which operates on a faster monthly cycle — has since shown sentiment collapse to an all-time record low of 48.2 in the May preliminary reading. McKinsey’s ConsumerWise quarterly data, when the Q2 2026 edition publishes, will likely show the sharpest single-quarter sentiment decline in the survey’s history. The gap between the McKinsey pre-war stability reading and the UMich post-war record low is the precise measure of what the Iran conflict has done to consumer confidence in 10 weeks.
The top consumer worries in the Q1 2026 ConsumerWise data: rising prices ranked first (43% of respondents), followed by tariff policies (29%). The tariff concern is notable — 91% of US consumers had heard about tariffs in the news or discussed them with others by early 2026, before the Iran war added energy prices as a dominant concern. In Q2, energy prices will almost certainly displace tariffs as the second-ranked worry, with rising prices remaining first.
The ConsumerWise data provides behavioral confirmation of what RBC Economics described theoretically in April and what Kraft Heinz and McDonald’s confirmed operationally in their earnings calls. McKinsey’s survey data shows that as consumers reported a decline in household savings in Q4 2025, the share taking active measures to manage financial pressure rose sharply:
The share of respondents who said they had dipped into savings to cover expenses rose three percentage points quarter-over-quarter. The share who had reduced the portion of their income allocated to savings also rose three percentage points. At least one in four respondents said they had used their credit cards more. At least one in four said they had cut back on food spending.
These four behaviors — savings drawdown, savings rate reduction, credit card increase, food spending reduction — are the precise sequence that precedes consumer credit deterioration. They are not leading indicators in the traditional sense. They are current behavioral admissions from a nationally representative consumer survey conducted by one of the most rigorous research organizations in the world. The sequence is happening now. The credit stress it produces follows with a 60-to-90-day lag.
The Gen Z data in the ConsumerWise report is the most directly relevant for non-bank consumer lenders and card issuers. McKinsey’s findings describe a generation that is simultaneously financially strained and behaviorally inconsistent in ways that create specific underwriting challenges.
On the strain side: Gen Z respondents reported fewer income gains than any other age group. They dipped into savings at higher rates than any other generation. A larger share cut back on food spending. A larger share increased credit card use. The LendingTree survey data from earlier this year confirmed the same pattern: 58% of Gen Z cardholders pay only the minimum balance, and 44% do not know their APR.
On the behavioral inconsistency: McKinsey’s Q4 2025 ConsumerWise data showed Gen Z as the only age group to report higher optimism (up six percentage points quarter-over-quarter) — described by McKinsey as “incongruous with their reported splurge intentions.” In the Q4 data, Gen Z simultaneously reported financial strain and intent to maintain or increase discretionary spending — a pattern that McKinsey researchers described as a “bifurcation within the generation” between a group adjusting to tighter finances and a group maintaining lifestyle despite financial constraints.
For consumer lenders, the Gen Z credit profile is the most complex in the population: high stress signals in behavioral data, high credit card utilization, low financial literacy, income below older generations, and a spending psychology that does not reliably respond to standard financial pressure signals. The traditional underwriting heuristics — income verification, payment history, utilization ratio — are necessary but not sufficient for this population. The behavioral inconsistencies McKinsey documents suggest that a Gen Z borrower with a clean payment history and moderate utilization may carry embedded stress risk that is not visible in the credit file.
The Q1 2026 ConsumerWise edition marked the first time McKinsey’s survey explicitly measured AI adoption in consumer financial decision-making. The preliminary data — reflecting early 2026 before the ChatGPT Personal Finance launch on May 15 — already showed meaningful adoption of generative AI tools for product research and financial comparisons. The McKinsey finding: what changed most materially in early 2026 was not how consumers felt about the economy, but how they gathered product information and made purchase decisions.
This finding arrives the same week that OpenAI launched ChatGPT Personal Finance — connecting 200 million monthly financial AI users to their actual bank account data through Plaid. The McKinsey pre-launch data already showed AI reshaping the consumer decision journey. The post-launch environment will accelerate that trend by orders of magnitude. McKinsey’s observation that AI is shifting the information-gathering phase of consumer decisions is the academic confirmation of what the OpenAI launch makes operationally real: the consumer’s financial decision journey now has an AI layer that precedes contact with any lender.
The income gradient is your risk map. McKinsey’s finding that income is the dominant variable in consumer confidence translates directly to portfolio risk. Your loss exposure is not distributed uniformly across your borrower base — it intensifies as borrower income falls. The stress indicators McKinsey documents (savings depletion, credit card reliance, food spending cuts) are concentrated in the lower income quintiles. If your portfolio segmentation does not reflect income distribution as a primary risk axis — not just FICO, not just employment status, but income — your reserve assumptions are likely not accurately capturing where the stress is concentrated.
The savings depletion behavioral data has a known credit lag. McKinsey’s survey captures the behavior (savings drawdown, credit card increase) at the time it is happening. The credit performance consequence follows approximately 60 to 90 days later in payment data. The Q4 2025 and Q1 2026 ConsumerWise data showing accelerating savings depletion translates to Q2 2026 delinquency data arriving in June and July reports. The McKinsey behavioral signal is the leading indicator. The lender portfolio data is the lagging confirmation. Use the leading indicator.
Gen Z is not a monolithic credit segment — it is two populations. McKinsey’s bifurcation-within-the-generation finding has direct underwriting implications. A Gen Z borrower with surface-level financial stability signals (moderate FICO, recent payment history) may belong to the “maintaining lifestyle despite constraints” cohort — which carries embedded deterioration risk not visible in the credit file. Building income stability, employment sector, and behavioral spending proxies into Gen Z underwriting models is not optional in the current environment. The income-confidence gradient McKinsey documents is steepest within Gen Z.
The AI reshaping of consumer decision-making requires a distribution strategy response, not just a technology response. McKinsey’s finding that AI is changing how consumers gather financial information — confirmed and amplified by the OpenAI Plaid launch — means that the consumer’s path to a loan application increasingly runs through an AI intermediary before it reaches any lender’s marketing funnel. The response is not simply to build better AI tools internally. It is to be present in the AI layer where consumers are making decisions — whether through direct integrations, partnership with AI platforms, or product positioning that performs well in AI-mediated comparisons. Lenders who treat AI as a back-office efficiency tool and miss the distribution shift will lose origination volume to those who understand that AI has moved to the front of the consumer decision journey.
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